Business analysis with your Snowflake data
Your Snowflake data warehouse can help teams investigate business changes and run recurring analysis with Databasin. We implement the source connections, business definitions and workflows around the warehouse you already use. People can ask questions about the prepared data and examine the SQL behind an answer.
Work with the warehouse already in place
We work around the Snowflake warehouse your organization already operates. If a review is waiting on data from another system, we implement that source connection and its model. If the records are already available, we can prepare the definitions and question interface needed to use them.
The connection route follows that job. Scheduled pipelines prepare and retain source records; a supported Snowflake connection also makes existing records available to Databasin for analysis. We establish where the data will be used, who can read it and how its updates fit the application.
Complete the data work around Snowflake
Design, Build, Run
We take responsibility for the work from defining the outcome through implementation and ongoing support.
Design
We define the outcome, current processes and expected return with your stakeholders. A working example shows how Databasin would answer your business questions.
Build
We get your first use case live in 90 days. Communication, rollout, training and success measurement are included in the work.
Run
Choose the help you need after launch. We can run the solution for you, provide monthly support hours or stay on call.
Results from customer work
- 20+ systems unifiedDatabasin brought WashU Medicine's financial data together.
- Infrastructure costs at 1/3 of the traditional approachWashU Medicine's result from changing its data infrastructure.
18%
Higher grant proposal success
Measured at a research institution working with Databasin.
“What used to take weeks or sometimes even months now happens in minutes.”
Support for connected Snowflake analysis
Existing records
Use existing Snowflake records through the connection configured for the application.
Source ingestion
Connect the operational sources that a planned Snowflake review still needs.
Effective dates
Resolve historical staffing and compensation values for the period named in the question.
Shared calculations
Reuse the defined calculations across reports and questions about the same measure.
Query evidence
Open the query to examine how an answer used the source records.
Example: Snowflake data in business reviews
Workforce costs
Review a department's financial activity alongside workforce history, using the assignments that applied during the period being examined.
Clinical activity
Make the required Epic records available for recurring clinical operations analysis in the organization's existing Snowflake environment.
Research analysis
Prepare the study and funding records needed for a research question, then examine them through the chosen analytical route.
What happens next
We would like to hear where your team wants to make progress with data and AI. We can discuss a project you have in mind or explore where Databasin could help with the work.
What happens next
Book a demo
Book a conversation about your organization and the work you want to improve. Questions about where to start are welcome.
Explore the opportunity
We show a working example that answers your business questions, then discuss what it would take to deliver it for your team.
Get the first result
After agreeing the first use case, we implement it with your team. We train the people using it and measure how it performs.
FAQ
Can Databasin query Snowflake without syncing the records first?
Yes. A live-federation connection can read Snowflake records without first syncing them. We use scheduled ingestion when the work needs to retain records.
Where does Databasin store the Snowflake key?
The key lives in Databasin's managed secret vault. When a process needs it as a file, the connector sets owner-only permissions before writing it and removes the file when the process exits. It does not put the private key in logs. These controls apply to the connector's key handling.
Can a Data App run directly on Snowflake?
Its supported engines are Trino, Databasin Sail and Databricks. We therefore establish the supported route for Snowflake records as part of the application design. That specifies the connection, where queries execute and the access used by the application before we build the team's review.
Can a Databasin investigation agent change Snowflake records?
Its production-source tools can only read. The agent can examine schema, issue SELECT queries and fetch results within the run's limits. Its SQL and execution record are available to inspect. A workflow can contain separately authorized transformation tasks, whose permissions are distinct from the investigation agent's access.
Can Databasin run in our own environment?
Yes. We can install Databasin in your Azure environment or use a hosted deployment. The implementation establishes the Snowflake connection and data location, together with the model-provider route. We work through those choices for the particular application and the people who will use its results.
Do our existing Snowflake reports have to change?
No. The work can focus on a missing source, a new business view or an additional application while established reports continue. We examine how the new measures relate to the existing ones so the team understands what each review represents and where its records come from.
Can you finish source work that has held up a Snowflake rollout?
Yes. Databasin has helped resolve stalled Snowflake source integration, including Epic data at a health system. Our team examines the unfinished connection and modeling work, then implements it around the business outcome. Deployment rescue describes how we approach that situation.
Discuss your Snowflake project
We would like to hear what your team wants to do with Snowflake and where the work stands today. We can discuss the sources, questions and recurring processes that would make the existing warehouse more useful to the business.